Cultural Competence

Bias reduction in representation of histopathology images using deep feature selection.

Appearing traces of bias in deep networks is a serious reliability issue which can play a significan...

Algorithmic bias in health care: Opportunities for nurses to improve equality in the age of artificial intelligence.

Age prediction by deep learning applied to Greenland halibut (Reinhardtius hippoglossoides) otolith images.

Otoliths (ear-stones) in the inner ears of vertebrates containing visible year zones are used extens...

Self-supervised machine learning for live cell imagery segmentation.

Segmenting single cells is a necessary process for extracting quantitative data from biological micr...

CerebNet: A fast and reliable deep-learning pipeline for detailed cerebellum sub-segmentation.

Quantifying the volume of the cerebellum and its lobes is of profound interest in various neurodegen...

Delay Compensation-Based State Estimation for Time-Varying Complex Networks With Incomplete Observations and Dynamical Bias.

In this article, a delay-compensation-based state estimation (DCBSE) method is given for a class of ...

International comparison of cross-disciplinary integration in industry 4.0: A co-authorship analysis using academic literature databases.

In innovation strategy, a type of Schumpeterian competitive strategy in business administration, "in...

Study on the Classification of Metal Objects by a Fluxgate Magnetometer Cube Structure.

After wars, some unexploded bombs remained underground, and these faulty bombs seriously threaten th...

Artificial intelligence and clinical anatomical education: Promises and perils.

Anatomy educators are often at the forefront of adopting innovative and advanced technologies for te...

Rationalized deep learning super-resolution microscopy for sustained live imaging of rapid subcellular processes.

The goal when imaging bioprocesses with optical microscopy is to acquire the most spatiotemporal inf...

Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images.

PURPOSE: Artificial intelligence (AI) has high diagnostic accuracy for coronary artery disease (CAD)...

Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning.

The number of patients with heart failure and related deaths is rapidly increasing worldwide, making...

Parallel Frequency Function-Deep Neural Network for Efficient Approximation of Complex Broadband Signals.

In recent years, with the growing popularity of complex signal approximation via deep neural network...

Openness and Transparency in the Evaluation of Bias in Artificial Intelligence.

Generalizability and Bias in a Deep Learning Pediatric Bone Age Prediction Model Using Hand Radiographs.

Background Although deep learning (DL) models have demonstrated expert-level ability for pediatric b...

From real-world electronic health record data to real-world results using artificial intelligence.

With the worldwide digitalisation of medical records, electronic health records (EHRs) have become a...

Can We Predict Clinical Pharmacokinetics of Highly Lipophilic Compounds by Integration of Machine Learning or In Vitro Data into Physiologically Based Models? A Feasibility Study Based on 12 Development Compounds.

While high lipophilicity tends to improve potency, its effects on pharmacokinetics (PK) are complex ...

Recover User's Private Training Image Data by Gradient in Federated Learning.

Exchanging gradient is a widely used method in modern multinode machine learning system (e.g., distr...

Jointly estimating bias field and reconstructing uniform MRI image by deep learning.

Bias field is one of the main artifacts that degrade the quality of magnetic resonance images. It in...

TAMC: A deep-learning approach to predict motif-centric transcriptional factor binding activity based on ATAC-seq profile.

Determining transcriptional factor binding sites (TFBSs) is critical for understanding the molecular...

Deep-TOF-PET: Deep learning-guided generation of time-of-flight from non-TOF brain PET images in the image and projection domains.

We aim to synthesize brain time-of-flight (TOF) PET images/sinograms from their corresponding non-TO...